Variable Selection for Correlated High-Dimensional Data with Infrequent Categorical Variables: Based on Sparse Sample Regression and Anomaly Detection Technology.
Yuhei KotsukaSumika ArimaPublished in: KES-IDT (2021)
Keyphrases
- variable selection
- anomaly detection
- high dimensional data
- high dimensional
- regression problems
- dimension reduction
- sparse representation
- dimensionality reduction
- low dimensional
- nearest neighbor
- model selection
- data sets
- high dimensionality
- data points
- data analysis
- linear discriminant analysis
- unsupervised learning
- regression model
- low rank
- data samples
- variable weighting
- sample size
- genetic programming
- graphical models
- association rules
- feature space
- reinforcement learning
- feature extraction
- computer vision
- genetic algorithm
- markov blanket
- neural network